Robots Meta Conflict
thedaviddias/Front-End-Checklist
A skill your agent uses when applies to sites that use both robots.txt disallow rules and meta robots noindex tags.
A skill your agent uses when judging whether a robotics project fits RSS (Robotics: Science and Systems), the single-track selective venue whose bar is a scientific claim about robotics, and when…
MITAuto-check passed
Install Rss Topic Selection
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill rss-topic-selection -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills rss-topic-selection --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/RSS-Skills/skills/rss-topic-selection .claude/skills/rss-topic-selection && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "rss-topic-selection" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/RSS-Skills/skills/rss-topic-selection into .claude/skills/rss-topic-selection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rss-topic-selection", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/RSS-Skills/skills/rss-topic-selectionType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill rss-topic-selection -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills rss-topic-selection --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/RSS-Skills/skills/rss-topic-selection .agents/skills/rss-topic-selection && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "rss-topic-selection" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/RSS-Skills/skills/rss-topic-selection into .agents/skills/rss-topic-selection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rss-topic-selection", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill rss-topic-selection -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills rss-topic-selection --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/RSS-Skills/skills/rss-topic-selection .cursor/skills/rss-topic-selection && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "rss-topic-selection" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/RSS-Skills/skills/rss-topic-selection into .cursor/skills/rss-topic-selection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rss-topic-selection", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/brycewang-stanford/Awesome-Journal-Skills.git --path RSS-Skills/skills/rss-topic-selection--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill rss-topic-selection -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills rss-topic-selection --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/RSS-Skills/skills/rss-topic-selection .gemini/skills/rss-topic-selection && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "rss-topic-selection" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/RSS-Skills/skills/rss-topic-selection into .gemini/skills/rss-topic-selection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rss-topic-selection", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills rss-topic-selectionInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill rss-topic-selection -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/RSS-Skills/skills/rss-topic-selection .github/skills/rss-topic-selection && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "rss-topic-selection" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/RSS-Skills/skills/rss-topic-selection into .github/skills/rss-topic-selection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rss-topic-selection", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill rss-topic-selection -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills rss-topic-selection --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/RSS-Skills/skills/rss-topic-selection .opencode/skills/rss-topic-selection && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "rss-topic-selection" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/RSS-Skills/skills/rss-topic-selection into .opencode/skills/rss-topic-selection/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "rss-topic-selection", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
rss-topic-selection- GitHub stars
- 1.2k
- Token cost
- ~1.7k tokens
- SKILL.md length
- 884 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when judging whether a robotics project fits RSS (Robotics: Science and Systems), the single-track selective venue whose bar is a scientific claim about robotics, and when…
- Works in 3 steps: Claim probe — write the contribution as… → Audience probe — RSS attendees span… → Compression probe — the 2026 format is 8…
- Judging whether a robotics project fits RSS (Robotics: Science and Systems)
- SKILL.md covers The one question RSS asks, Routing table (from RSS's seat), Three-part fit probe and Worked micro-decision, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Rss Topic Selection is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when judging whether a robotics project fits RSS (Robotics: Science and Systems), the single-track selective venue whose bar is a scientific claim about robotics, and when routing instead toward ICRA, IROS, CoRL, HRI, WAFR, T-RO, or IJRR based on claim type, evidence shape, and audience.
Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. ｜ 覆盖主流期刊的… The licence is MIT.
When your agent uses it
- Judging whether a robotics project fits RSS (Robotics: Science and Systems)
- The single-track selective venue whose bar is a scientific claim about robotics
- When routing instead toward ICRA
- IJRR based on claim type
Example prompts
- “/rss-topic-selection”
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- Claim probe — write the contribution as a single declarative sentence with no
- Audience probe — RSS attendees span planning, perception, learning, control,
- Compression probe — the 2026 format is 8 pages excluding references, a ceiling
What it can do on your machine
Read from SKILL.md and the folder at commit 932eb23. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Rss Topic Selection loads about 1.7k tokens when it runs. Until then it costs about 78 tokens; SKILL.md has 884 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 884 words, ~1,701 tokens.
Download SKILL.mdSave it as
.claude/skills/rss-topic-selection/SKILL.md (or your agent's skills folder).- name
- rss-topic-selection
- description
- Use when judging whether a robotics project fits RSS (Robotics: Science and Systems), the single-track selective venue whose bar is a scientific claim about robotics, and when routing instead toward ICRA, IROS, CoRL, HRI, WAFR, T-RO, or IJRR based on claim type, evidence shape, and audience.
RSS Topic Selection
Decide whether the project belongs at RSS before any writing starts. RSS is the deliberately small, single-track robotics conference run under the RSS Foundation: every accepted paper is presented to the entire audience, so the program committee selects for work the whole field should hear about. That structure creates the venue's distinctive question, and this skill applies it.
The one question RSS asks
What does this paper claim about robotics — as science — that was not known before?
- A property proved about a class of planners; a measured bottleneck the community misattributed; a representation whose suitability for robot data is argued and then tested; a capability shown to transfer for a stated reason — all RSS-shaped.
- "We integrated known components and the system works well" is a legitimate result, but it is a systems demonstration, and at RSS it must still carry an insight: what does the integration reveal that component papers could not?
- The 2026 CFP welcomes both Science and Systems contributions; the shared requirement is a contribution statement a skeptic could test, not a capabilities inventory.
Routing table (from RSS's seat)
| If the project is... | Verdict | Rationale |
|---|---|---|
| One sharp idea + evidence sized to it | RSS core | Single-track audience rewards concentrated novelty |
| A broad integrated platform, many components, no isolable insight | ICRA / IROS | Higher-volume multi-track programs absorb breadth |
| Learning-centric, benchmark-driven, embodiment secondary | CoRL | Robot-learning community is the right jury |
| Human-subject study as the main evidence | HRI | Study-design reviewing lives there |
| Pure algorithmic-foundations result, no experiment planned | WAFR or a theory venue | RSS still expects an empirical anchor |
| Needs 15+ pages of proofs or longitudinal experiments | T-RO / IJRR | Journal length; RSS caps at 8 pages excl. references (2026) |
Three-part fit probe
Run these in order; failing any one is a re-route signal, not a death sentence:
- Claim probe — write the contribution as a single declarative sentence with no system name in it. If the sentence is empty without the system name, the insight is not yet separable from the artifact.
- Audience probe — RSS attendees span planning, perception, learning, control, and design. Would a session chair from a different subfield still care? If the result matters only inside one benchmark community, CoRL or a workshop is kinder.
- Compression probe — the 2026 format is 8 pages excluding references, a ceiling the CFP explicitly frames as not a target. If the argument cannot be made crisply, the project may be a journal paper wearing conference formatting.
Worked micro-decision
A team has a legged robot climbing unstructured rubble using a new terrain-contact estimator plus an off-the-shelf controller. As a platform story it routes to ICRA. But if they can show the estimator's confidence signal predicts failures two footsteps ahead — and that this predictive structure, not raw accuracy, is what enables recovery — they now own a falsifiable claim about proprioceptive sensing, and RSS becomes the natural home. Same hardware, different paper.
Show full SKILL.md (404 more words)Show less
Claim taxonomy: what an RSS-shaped assertion looks like
Concrete templates a project can aim to instantiate — each is falsifiable and system-name-free:
- Property claim — "planners of class C converge to suboptimal solutions; variant C' restores optimality." (The theorem-first lane.)
- Bottleneck claim — "in task family T, failures are dominated by factor F, not the factor the literature optimizes."
- Representation claim — "encoding the problem as R suits robot data because of property P, and evidence across tasks/platforms bears P out."
- Transfer claim — "capability K generalizes across E for stated reason R, and breaking R breaks the transfer."
- Measurement claim — "the community's standard metric M mis-ranks methods under condition X; here is the corrected instrument."
If none of these templates fits even loosely, the project is probably a systems report or an application study — respectable, but routed elsewhere.
Signals to weigh before committing the January slot
| Signal | Reading |
|---|---|
| The team can state the claim without naming the robot | Strong RSS signal |
| The most exciting artifact is a video, not a finding | Demo gravity — reframe or reroute |
| Reviewers from planning AND learning would both engage | Whole-audience fit confirmed |
| Evidence exists only in simulation, claim mentions the world | Close the gap or scope the claim |
| The natural length is 14 pages | Journal-shaped; consider T-RO/IJRR |
| The idea would still matter if the success rate were 20% lower | Insight-driven, not benchmark-driven |
Cycle discipline
- Scope emphasis and paper-type wording shift per edition; reread the current CFP (roboticsconference.org/information/cfp/) before the final call.
- Deadline geometry matters for routing: RSS 2026 closed in late January for a July
conference; ICRA and CoRL sit elsewhere in the year — see
rss-workflowfor the full calendar argument. - The Science/Systems paper-type wording was specific to the 2026 CFP; confirm the current cycle's categories before framing the contribution statement around them.
When RSS is the wrong home for excellent work
Fit failure is not quality failure. Recognize these honorable mismatches early:
- A superbly engineered platform whose lessons are in the integration details — the field needs it published, at ICRA/IROS length and breadth.
- A benchmark or dataset whose value is adoption, not insight — a track designed for artifacts (or a journal) serves it better than a single-track talk slot.
- A result whose proof apparatus dwarfs its empirical story — WAFR or a journal gives the proofs room the 8-page ceiling cannot.
- Work whose audience is one application community (agriculture, surgery, logistics) — the domain venue's reviewers can evaluate what RSS's generalists cannot.
Output format
[RSS verdict] core fit / fixable framing / re-route
[Scientific claim] <one sentence, no system name>
[Whole-audience hook] <why a distant subfield cares>
[Evidence-to-claim gap] <what is missing>
[If re-route] ICRA / IROS / CoRL / HRI / WAFR / T-RO / IJRR + one-line reason© brycewang-stanford, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in RSS-Skills/skills/rss-topic-selection of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Rss Topic Selection next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Rss Topic Selection this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.7k | Automated safety check: Pass | MIT | |
| Robots Meta Conflictthedaviddias/Front-End-Checklist | 74k | — | ~555 | Automated safety check: Pass | MIT | |
| Robot Framework Skillsickn33/agentic-awesome-skills | 47k | 1 repos | ~1.4k | Automated safety check: Pass | MIT | |
| Robots Metathedaviddias/Front-End-Checklist | 74k | — | ~494 | Automated safety check: Pass | MIT | |
| Robots Txtthedaviddias/Front-End-Checklist | 74k | — | ~483 | Automated safety check: Pass | MIT | |
| Table Fitasgeirtj/system_prompts_leaks | 69k | — | ~772 | Automated safety check: Pass | CC0-1.0 |
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Questions about Rss Topic Selection
What does Rss Topic Selection do?
A skill your agent uses when judging whether a robotics project fits RSS (Robotics: Science and Systems), the single-track selective venue whose bar is a scientific claim about robotics, and when…. Rss Topic Selection is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when judging whether a robotics project fits RSS (Robotics: Science and Systems), the single-track selective venue whose bar is a scientific claim about robotics, and when routing instead toward ICRA, IROS, CoRL, HRI, WAFR, T-RO, or IJRR based on claim type, evidence shape, and audience.
When should I use Rss Topic Selection?
Rss Topic Selection fits situations like: judging whether a robotics project fits RSS (Robotics: Science and Systems); the single-track selective venue whose bar is a scientific claim about robotics; when routing instead toward ICRA; IJRR based on claim type.
How do I install Rss Topic Selection in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill rss-topic-selection -a claude-code`. Or copy the skill folder (RSS-Skills/skills/rss-topic-selection in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/rss-topic-selection in your project. Claude Code loads it when a task matches its description.
How do I install Rss Topic Selection in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill rss-topic-selection -a codex`. Or copy the skill folder (RSS-Skills/skills/rss-topic-selection in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/rss-topic-selection in your project. Codex loads it when a task matches its description.
Can I use Rss Topic Selection in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill rss-topic-selection -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/rss-topic-selection, .gemini/skills/rss-topic-selection, .github/skills/rss-topic-selection and .opencode/skills/rss-topic-selection in your project.
What does Rss Topic Selection need to run?
SKILL.md names no scripts, command-line tools or credentials: Rss Topic Selection is instructions for the agent only.
Does Rss Topic Selection access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Rss Topic Selection safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Rss Topic Selection use?
Rss Topic Selection is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Rss Topic Selection use?
About 1.7k tokens (SKILL.md is roughly 6.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Rss Topic Selection?
Skills that share tags, products or a category with Rss Topic Selection: Robots Meta Conflict (thedaviddias/Front-End-Checklist, 74k stars), Robot Framework Skill (sickn33/agentic-awesome-skills, 47k stars), Robots Meta (thedaviddias/Front-End-Checklist, 74k stars) and Robots Txt (thedaviddias/Front-End-Checklist, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Rss Topic Selection?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,216 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.
Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.